Special Issue "Mathematical Model and Computation in Geotechnical Engineering"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 20 September 2021.

Special Issue Editors

Prof. Dr. Chongchong Qi
E-Mail Website
Guest Editor
School of Resources and Safety Engineering, Central South University, Changsha 410012, China
Interests: cemented paste backfill(CPB); utilization of inorganic waste and residues; green or sustainable mining; materials science, especially cementitious materials; artificial intelligence; big data
Special Issues and Collections in MDPI journals
Prof. Dr. Wengang Zhang
E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing, China
Interests: big data and machine learning for geoscience and geoengineering; geotechnical reliability analysis and risk assessment; transparent soil model testing

Special Issue Information

Dear Colleagues,

It is widely known that within geotechnical engineering exists various uncertainties, resulting in many troubles when studying the reliability or risk assessment of geotechnical structures. Modelling the behavior of such uncertainties is complex and sometimes beyond the capability of traditional methods. In recent years, the applications of state-of-the-art methods, such as artificial intelligence (AI), machine learning (ML), big data and other advanced mathematical models, in a wide range of geotechnical engineering, have increased rapidly. For example, AI can be very useful in solving problems where deterministic solutions are not available or are excessively expensive in terms of computational cost, but for which there are significant observations and data available. This Special Issue contains original and hitherto unpublished works on the applications of AI, ML, big data, reliability algorithms and probabilistic risk analysis (PRA) in geotechnical engineering. We invite you to send original articles on topics, including, but not limited to:

New and improved reliability algorithm and design;

Geotechnical data optimization and mining;

Applications of AI or ML in geotechnical engineering;

Geotechnical risk assessment and management;

Geotechnical probabilistic problems;

Novel experiment and numerical simulation in geotechnical engineering

Prof. Dr. Chongchong Qi
Prof. Dr. Zhang Wengang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • new and improved reliability algorithm and design
  • geotechnical data optimization and mining
  • applications of AI or ML in geotechnical engineering
  • geotechnical risk assessment and management
  • geotechnical probabilistic problems
  • novel experiment and numerical simulation in geotechnical engineering

Published Papers (1 paper)

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Research

Article
Comparison of Dynamic Characteristics between Small and Super-Large Diameter Cross-River Twin Tunnels under Train Vibration
Appl. Sci. 2021, 11(16), 7577; https://doi.org/10.3390/app11167577 - 18 Aug 2021
Viewed by 164
Abstract
Train vibration from closely aligned adjacent tunnels could cause safety concerns, especially given the soaring size of the tunnel diameter. This paper established a two-dimensional discrete element model (DEM) of small (d = 6.2 m) and super-large (D = 15.2 m) [...] Read more.
Train vibration from closely aligned adjacent tunnels could cause safety concerns, especially given the soaring size of the tunnel diameter. This paper established a two-dimensional discrete element model (DEM) of small (d = 6.2 m) and super-large (D = 15.2 m) diameter cross-river twin tunnels and discussed the dynamic characteristics of adjacent tunnels during the vibration of a train that runs through the tunnel at a speed of 120 km/h. Results in the D tunnel showed that the horizontal walls have the same horizontal displacement (DH) and the vertical walls have the same vertical displacement (DV). The stress state of the surroundings of the D tunnel is the decisive factor for DH, and the distance from the vibration point to the measurement point is the decisive factor for DV. Results in the comparison of the d and D tunnels showed that the D tunnel is more stable than the d tunnel with respect to two aspects: the time the tunnel reaches the equilibrium state and the vibration amplitude of the structure’s dynamic and static responses. The dynamic characteristic of the d and D tunnel is significantly different. This research is expected to guide the design and construction of large diameter twin tunnels. Full article
(This article belongs to the Special Issue Mathematical Model and Computation in Geotechnical Engineering)
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